Lung water content measurement system and calibration method

ABSTRACT

A system and method for monitoring lung water content of a patient. The system may include microwave sensors and a processor. The system may transmit microwave signals into, and receive microwave signals from, the thorax of a patient using the microwave sensors. The received microwave signals may each have at least one frequency component with a magnitude and a phase. The system may analyze the phase of the received microwave signal corresponding to a first pair of the microwave signals to monitor changes in the lung water content. The system may analyze the magnitude of the received microwave signal corresponding to a second, different pair of the microwave sensors to determine whether the lung water content is increasing or decreasing. The system may also analyze the received microwave signals to determine a blood pressure indicator and to determine lung water content.

INCORPORATION BY REFERENCE TO ANY PRIORITY APPLICATIONS

Any and all applications for which a foreign or domestic priority claimis identified in the Application Data Sheet as filed with the presentapplication are hereby incorporated by reference under 37 CFR 1.57. Inparticular, this application claims priority to U.S. Provisional PatentApplication 62/115,549, filed Feb. 12, 2015, and entitled “Multi-Sensorand Automated Segmented Calibration Method,” and to U.S. ProvisionalPatent Application 62/196,871, filed Jul. 24, 2015, and entitled “LUNGWATER CONTENT MEASUREMENT SYSTEM AND CALIBRATION METHOD,” both of whichare hereby incorporated by reference in their entireties.

STATEMENT REGARDING FEDERALLY SPONSORED R&D

This invention was made with government support under Grant No. R21HL124457 awarded by the National Institutes of Health, and under GrantNos. IIP1127956 and OISE1059673 awarded by the National ScienceFoundation. The government has certain rights in the invention.

BACKGROUND Field

This disclosure relates to a non-invasive microwave instrument with anarray of microwave sensors. The microwave system can be used forcollecting, analyzing, and displaying physiological information.

Description of the Related Art

Improving healthcare is one of the most pressing challenges facing theworld in the 21st century. In order to meet this challenge, there is aneed for patient monitoring systems to track a variety of vital signs(VS), including lung water content (LWC). LWC is a medically-importantparameter because it can be used, for example, to reliably detect heartfailure and pulmonary edema at early stages.

SUMMARY

In some embodiments, a method of monitoring lung water content of apatient using at least two microwave sensors comprises: transmitting oneor more microwave signals into the thorax of a patient using one or moremicrowave sensors; receiving one or more of the microwave signals usingone or more microwave sensors, the one or more received microwavesignals each comprising at least one frequency component having amagnitude and a phase; analyzing the phase of one or more receivedmicrowave signals to monitor changes in the lung water content; andanalyzing the magnitude of one or more received microwave signals todetermine whether the lung water content is increasing or decreasing.

In some embodiments, a system for monitoring lung water content of apatient comprises: at least two microwave sensors; and a processorconfigured to perform a method comprising transmitting one or moremicrowave signals into the thorax of a patient using one or more of themicrowave sensors; receiving one or more of the microwave signals usingone or more of the microwave sensors, the one or more received microwavesignals each comprising at least one frequency component having amagnitude and a phase; analyzing the phase of one or more receivedmicrowave signals to monitor changes in the lung water content; andanalyzing the magnitude of one or more received microwave signals todetermine whether the lung water content is increasing or decreasing.

In some embodiments, a system for monitoring a physiologicalcharacteristic of a patient comprises: more than two microwave sensors;and a processor configured to perform a method comprising measuringmicrowave scattering parameters from the microwave sensors, themicrowave scattering parameters comprising at least microwavetransmission coefficients respectively corresponding to a selected firstmicrowave sensor and at least a second microwave sensor and a thirdmicrowave sensor; analyzing the measured microwave transmissioncoefficients to determine the physiological characteristic.

In some embodiments, a system for monitoring lung water content of apatient comprises: at least two microwave sensors; and a processorconfigured to perform a method comprising transmitting one or moremicrowave signals into the thorax of a patient using one or more of themicrowave sensors; receiving a first waveform corresponding to a firstpair of the microwave sensors; analyzing at least one characteristic ofthe first waveform to determine a physiological characteristic.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram illustrating a cardio-pulmonary (CP)microwave stethoscope measurement method and device configuration.

FIG. 2 illustrates conversion of the returned microwave measurementsignal into various critical measurement displays provided by thesystem.

FIG. 3 shows the transmission Sensor-1 and reception Sensor-2 carried ona substrate in side-by-side configuration.

FIG. 4 shows a preferred example of the microwave transmission sensorwith an adapter connector to a feeder coaxial cable.

FIG. 5 shows an alternative structure for the microwave transmissionsensor with a direct coaxial cable feeding structure.

FIG. 6A is a schematic illustration of a model which can be used todesign the impedance characteristics of a microwave sensor when it iscoupled to the body of a patient.

FIG. 6B shows a cross-sectional view through the microwave sensor at theline A-A in FIG. 6A.

FIGS. 6C and 6D illustrate the improved energy coupling characteristicsof the microwave sensors described herein as contrasted with primarilyradiating structures, such as antennas.

FIG. 7 shows the transmission and reception sensors mounted inside-by-side configuration in contact with the patient's chest.

FIG. 8 includes a graph which illustrates that a transmissioncoefficient signal (e.g., the phase component of the signal) can beanalyzed to determine respiration rate, heart rate, stroke volume,cardiac output, and lung water content.

FIG. 9 illustrates how several physiological parameters can becalculated from a transmission coefficient signal (e.g., the phasecomponent of the signal), such as the one illustrated in FIG. 8.

FIG. 10 includes a pair of graphs which show the sensitivity of thephase of the transmission coefficient (lower graph) when compared to thepulmonary artery pressure (upper graph) in a subject.

FIG. 11 illustrates an example of the placements of microwave sensors onthe thorax of a human for a monitoring system that includes an array ofmicrowave sensors.

FIG. 12 includes a graph of the magnitude and phase of the transmissioncoefficient between the fifth and sixth microwave sensors illustrated inFIG. 11. These phase and magnitude changes are shown as a function ofdeveloping edema (increasing water content) in a lung. An increase inlung water content corresponds to an increase in the signal attenuation(increase in −dB) as the signal travels through the lung.

FIG. 13 includes a graph of the magnitude and phase of the transmissioncoefficient between the seventh and sixth microwave sensors illustratedin FIG. 11. Once again, the graph shows changes in the magnitude andphase of the transmission coefficient with an increase in the watercontent in a lung. The magnitude shows the increase in attenuation withincreasing edema, while the relative phase of the transmissioncoefficient shows a trend opposite to the one measured between the fifthand sixth microwave sensors, as shown in FIG. 12.

FIG. 14 includes a graph of the magnitude and phase of the transmissioncoefficient between the seventh and eighth microwave sensors illustratedin FIG. 11. The trends of the magnitude and phase measured between theseventh and eighth microwave sensors are similar to those measuredbetween the fifth and sixth microwave sensors, as shown in FIG. 12.

FIG. 15 includes a graph of the magnitude and phase of the transmissioncoefficient between the sixth and seventh microwave sensors illustratedin FIG. 11. These phase and magnitude changes are shown as a functionfirst of increasing edema and then decreasing edema in a lung.

FIG. 16 is a chart of the magnitude and phase of the complete set ofscattering parameters for a monitoring system which includes an array ofmicrowave sensors.

FIG. 17 includes a graph of a transmission coefficient signal (e.g., thephase component of the signal) corresponding to a heart waveform for adialysis patient. The graph shows that the magnitude and shape of theheart waveform changes with changing blood pressure during the dialysisprocess.

FIGS. 18A and 18B also show clinical data collected from a dialysispatient using the microwave system described herein.

FIG. 19 shows a graphical representation of Starling's Law andillustrates how the microwave system described herein can be used toassist in treatment of patients with congestive heart failure orpatients undergoing dialysis.

DETAILED DESCRIPTION

Certain preferred embodiments of a microwave medical monitoringinstrument are described in detail below. The instrument monitorsphysiological information by transmitting microwaves into a patient'sthorax using microwave sensors, and then measuring microwave scatteringparameters, also using microwave sensors. The instrument is anintegrated, multipurpose low-cost and non-invasive system, with multiplemicrowave sensors, which can be used for conveniently monitoring thepatient condition (e.g., on a mobile device). The system is designed andequipped with digital signal processing algorithms for making multiplevital sign (VS) measurements, including lung water content (LWC),respiration rate (RR), respiration amplitude (RA), heart rate (HR),heart-beat amplitude (HA), stroke volume (SV), cardiac output (CO), andothers. Some aspects of the microwave medical monitoring instrument aredescribed in U.S. patent application Ser. No. 14/261,884, filed Apr. 25,2014, and entitled “MICROWAVE STETHOSCOPE FOR MEASURING CARDIO-PULMONARYVITAL SIGNS AND LUNG WATER CONTENT,” which is hereby incorporated byreference herein in its entirety.

By way of background, FIG. 1 is a schematic diagram which illustrates acardio-pulmonary (CP) microwave stethoscope measurement method anddevice configuration employing a sensor array comprised of N microwavetransmission/reception sensors placed on a patient's chest inspaced-apart configuration for taking integrated vital signs (VS) andlung water content (LWC) and other critical measurements. In someembodiments, the value of N is greater than two and depends upon theparticular monitoring application for which the system is being used.Sensor-1, Sensor-2, and Sensor-N are microwave sensors which can couplemicrowaves into and out of the body. A radio-frequency (RF) module 10 isused to send a microwave signal to the transmission Sensor-1 whichtransmits the signal through the skin and tissues of the thorax inposition at a patient heart-lung location, and receives a returnedscattered microwave signal at the reception Sensor-2 and/or Sensor-Nwhich is returned to the RF module 10. Conversely, Sensor-2 or Sensor-Ncan be used to transmit a signal through the skin and tissues of thethorax to Sensor-1.

The signal transmission and reception is controlled by a microcontroller12 which may be incorporated with or in a separate unit from the RFmodule 10. The microcontroller 12 includes an analog-to-digital (A/D)signal converter, and digital signal processing (DSP) capability foranalyzing the returned microwave signals and converting them to vitalsigns measurements. A wireless (e.g., Bluetooth) communicationcapability may be provided to send output data by wireless transmissionto a display 20. For remote and/or home-based patient monitoring, thedisplay 20 may be a smartphone display operated by a client displayapplication (smartphone app).

FIG. 2 illustrates conversion of the returned measurement signal intovarious clinical measurement displays provided by the system, such asLung Water, Respiration (BrPM), Heartbeat (BPM), and Stroke Volumedisplays.

FIG. 3 shows a microwave transmission Sensor-1 and reception Sensor-2embedded on patch substrates 34 in side-by-side configuration on a baselayer 35 for mounting them on the skin on a patient's chest. Asdiscussed herein, the base layer 35 can include additional microwavesensors arranged in an array. A preferred design for the microwavesensors is a coplanar waveguide structure with a center micro line stripin a central aperture that is carried on a substrate. The variousmicrowave sensors may be of the same design or different designs. Twoadjacent sensors are spaced apart by a spacing distance D, which ischosen to minimize or reduce electromagnetic (EM) coupling between theproximate conductive edges of the sensors and to maximize or increasesignal-to-noise ratio (SNR) of the returned signal. In some embodiments,the separation distance D is about 1-3 cm. Larger separations may befound to result in weaker signals (low SNR) and closer separations mayresult in a strong electromagnetic (EM) coupling between the sensors andreduce sensitivity to vital signs and changes in lung water content.

FIG. 4 shows a preferred example for a microwave sensor having a coaxialcable feed line 33 a connected to a microstrip center conductor 31positioned in a central aperture of and terminating in a resistive (e.g.50 ohm) termination 36 in electrical contact with a metal conductorground plane 32. The sensor is shown with length-width dimensions of 34mm×32 mm for illustration.

FIG. 5 shows an alternative structure for a microwave sensor having anadapter (SMA) connector for a coaxial cable connection to the microstripcenter conductor 31. The sensor is shown with length-width dimensions of36 mm×32 mm for illustration.

Each microwave sensor can be designed so as to couple microwaveradiation into the body of a patient in a localized region about theapproximate footprint of the microwave sensor with relatively littleleakage into the air or outside this footprint. Localized coupling ofmicrowave radiation into a patient's body at the specific location ofeach microwave sensor helps reduce external signal leakage and mutualcoupling of non-physiological information carrying signals amongstsurrounding sensors. If a signal from a transmitting microwave sensorcan propagate to a receiving microwave sensor without the transmittedenergy first having interacted with the physiological structures orprocesses which are desired to be monitored, then the received energywill in general not be useful in providing physiological informationabout the patient but will instead tend to obscure signals which docarry physiological information. Localized coupling of microwaveradiation into the body within the approximate footprint of eachmicrowave sensor can be particularly important in embodiments whichinclude arrays of several sensors, as described further herein. This istrue because larger numbers of microwave sensors in the sensing arraycan potentially lead to increased opportunities for external leakage andundesired mutual coupling between microwave sensors.

In some embodiments, localized coupling of microwave energy into thebody within the approximate footprint of each microwave sensor can beimproved by designing each microwave sensor to exhibit impedancematching characteristics while in the as-worn measurement positionproximate to the body of a patient (e.g., while the microwave sensor isin contact with skin, muscle, tissue, etc.). In other words, eachmicrowave sensor can be designed so as to be substantially impedancematched with the feeding transmission line when coupled to the body ofthe patient rather than being substantially impedance matched to thefeed line while located in free space without considering the effect ofthe patient's body on the impedance characteristics of the microwavesensor. In some embodiments, the feeding transmission line (e.g., thecoaxial cable 33 a) can have a characteristic impedance of, for example,50Ω or 75Ω. In such embodiments, the microwave sensor can be designed toexhibit a substantially matched impedance when the sensor is coupled tothe body of the patient.

FIG. 6A is a schematic illustration of a model which can be used todesign the impedance characteristics of the microwave sensor 600 when itis coupled to the body of a patient. As discussed herein, in someembodiments the microwave sensor 600 can have a planar coaxialtransmission line design having a center conductor 602 which spans anaperture formed in a coplanar ground plane 604. The central conductor602 can be fed at one end by, for example, a coaxial line and can beterminated at the opposite end by a resistor.

FIG. 6B shows a cross-sectional view through the microwave sensor 600 atthe line A-A. As shown in the cross-sectional view, the center conductor602 and the coplanar ground plane 604 of the microwave sensor 600 can bemodeled as a metal, such as copper. “Region 1” above the centerconductor 602 and coplanar ground plane 604 of the microwave sensor 600can be modeled as a substance having an electrical permittivity ε_(r1).Meanwhile, “Region 2” below the microwave sensor can be modeled as asubstance having an electrical permittivity ε_(r2). In some embodiments,Region 1 represents air and Region 2 represents the body of a patient.(An intervening substrate layer can also be modeled between theconductors and Region 2.) Therefore, ε_(r1) can be given the value ofthe permittivity of air whereas ε_(r2) can be given the value of thepermittivity of skin, muscle, or tissue. According to this model, thecharacteristic impedance Z₀ of the microwave sensor 600, in the as-wornposition coupled with the body of the patient, can be calculatedaccording to the following example equations:

$Z_{0} = {\left( {60\pi} \right)\frac{K^{\prime}}{K\sqrt{\left( {ɛ_{r_{1}} + 1} \right)\left( {ɛ_{r_{2}} + 1} \right)}}}$$k = \frac{w}{w + {2g}}$ $k^{\prime} = \sqrt{1 - k^{2}}$where K can be calculated from the complete elliptic integrals of k, K′can be calculated from the complete elliptic integrals of k′, and wherew is the width of the center conductor 602 and g is the gap between thecenter conductor 602 and the ground plane 604.

As already discussed, the characteristic impedance Z₀ of the microwavesensor 600 while in the as-worn position coupled with the body of thepatient can be substantially matched to the characteristic impedance ofthe feed line. This results in reduced reflections and standing wavesand, consequently, improved localized coupling of microwave energy intothe body of the patient. FIG. 6B illustrates an example microwave sensor600 with dimensions calculated so as to exhibit matched impedancecharacteristics with a 50Ω feed line while the microwave sensor 600 iscoupled to the body of a patient. In the illustrated embodiment, thetransverse dimension, a, of the microwave sensor 600 can beapproximately 52.4 mm, while the longitudinal dimension, b, can beapproximately 35.4 mm. The gap, g, between the center conductor 602 andthe ground plane 604 can be approximately 9.9 mm, while the width, w, ofthe center conductor can be approximately 1.6 mm. It should beunderstood, however, that these dimensions merely represent an exampleembodiment and that many other embodiments are possible depending uponthe specific application.

FIGS. 6C and 6D illustrate the improved energy coupling characteristicsof the microwave sensors described herein as contrasted with primarilyradiating structures, such as antennas. FIG. 6C includes cross-sectionalviews of simulated electrical fields resulting from antennas (left) ascompared to the microwave sensors (i.e., electromagnetic (EM) couplers)described herein (right). Three separate cases are shown: a singletransmitting device (top), transmitting and receiving devices in aside-by-side configuration with a 10 mm gap (middle), and transmittingand receiving devices in a side-by-side configuration with a 20 mm gap(bottom). As illustrated, antennas result in a much more significantamount of external leakage into the air and stronger mutual couplingbetween neighboring devices, whereas the microwave sensors describedherein are significantly more effective in coupling microwave energyinto the tissue in a localized manner. FIG. 6D shows top views of thesame simulations from FIG. 6C. Once again, it is evident from FIG. 6Dthat the microwave sensors described herein are significantly moreeffective at coupling microwave energy into the tissue in a localizedmanner within the general footprint of the sensors.

In addition, the microwave sensors described herein have an advantageover antennas in that they can be based on transmission lines ratherthan primarily radiating structures. This is beneficial because itallows greater flexibility in terms of controlling the penetration depthof energy into the patient's body, as the transmission line-basedmicrowave sensors described herein can more readily be operated atdifferent frequencies. In transmission line-type microwave sensors, thesize of the sensor is not necessarily determined by the operatingfrequency. In contrast, the size of radiating structures such asantennas is much more dependent on the operating frequency. Operatingthe transmission line-type microwave sensors at different frequenciesfacilitates retrieval of information at different depths inside thepatient's body, where at higher frequencies the received informationwill be dominated by surface information and at lower frequencies thereceived information will be dominated by depth characteristics.

The fact that the microwave sensors described herein can be based ontransmission line technology rather than radiating antenna technologymeans that they can have dimensions that are substantiallyfrequency-independent. Instead, the size of the transmission line-basedmicrowave sensors described herein can be largely based on the size ofthe area of contact between the sensor and patient needed to facilitateadequate energy coupling into the patient's body of a quasi-transverseelectromagnetic mode guided between two conductors in a transmissionline design. Thus, microwave sensors that are roughly the size of EKGpatches can be capable of operating at frequencies as low as 700 MHz oras high as several GHz. This offers broadband capability to monitorsurface as well as depth information, such as lung water content.

FIG. 7 shows transmission and reception sensors mounted in side-by-sideconfiguration in contact with the patient's chest. In an example of theside-by-side sensor unit, the microwave transmission sensor has acoplanar waveguide structure that is fabricated on a flexible substrate.In determining an optimum operating frequency for the microwavetransmission sensor, tradeoffs may be made between desired depth ofpenetration in the human body (low frequency) and sensitivity to phasechanges (high frequency). A preferred frequency range is from 700 MHz to1.5 GHz, with an optimal range in the FCC allocated frequencies of 915MHz and 920 MHz for medical and industrial applications (ISM band). Forintegrated vital signs detection that includes surface (EKG) andsub-surface (lung water and cardiac activity) measurements, it may beadvantageous to use broadband sensors and multi-frequency measurementsto better identify and possibly separate the various signals. Withbroadband sensors, the signal coefficients can be measuredsimultaneously at multiple frequencies, enabling monitoring of apatient's body at various penetration depths and eliciting maximummedical information.

As discussed in U.S. patent application Ser. No. 14/261,884 (alreadyincorporated by reference herein in its entirety), experimental resultsshow that a separation distance of a few centimeters betweenside-by-side (SS) microwave sensors provides a good balance between SNRand sensitivity to vital signs. The side-by-side sensor configurationcan be further optimized with adjustments in electromagnetic energycoupler design, including good impedance match between the microwavefeed and sensor (e.g., while the sensor is in the as-worn positioncoupled to the patient's body), better energy distribution along thearea of contact, insensitivity to human and other surrounding object'smovements, and broadband characteristics.

As discussed herein, two or more microwave sensors can be provided in anarray and each sensor can be used to transmit signals to, or receivesignals from, any sensor in the array. These signals can be referred toas scattering parameter signals, which include transmission coefficientsignals and reflection coefficient signals. A signal transmitted fromone microwave sensor and received by another microwave sensor in thearray can be referred to as a transmission coefficient signal. A signaltransmitted and received at the same microwave sensor can be referred toas a reflection coefficient signal. In general, each signal can have aphase component and a magnitude component. These signals and/or thereconstituent components can be analyzed individually or collectively todetermine a variety of physiological information about the patient. Thisis particularly true in the case of the described microwave sensors, asmuch of the received signals in the transmission coefficientmeasurements modes and the modification of the reflection coefficientvalues result from the interaction with and the scattering from theinternal organs and tissue condition in the patient body, rather thandirect and mutual coupling between measuring devices. Localizingelectromagnetic energy coupling to the human body and reducing orminimizing mutual coupling between measuring devices can be importantfor achieving clear and uncorrupted data for the tissue conditions andstatus of internal organs.

FIG. 8 includes a graph 810 which illustrates that a transmissioncoefficient signal (e.g., the phase component of the signal) can beanalyzed to determine, for example, respiration rate, heart rate, strokevolume, cardiac output, and lung water content. The graph 810 includes acurve 820 which plots the phase of the transmission coefficient betweentwo microwave sensors in the side-by-side configuration illustrated inFIG. 7 as a function of time. Changes in the shape and characteristicsof the waveform can be analyzed to calculate various physiologicalparameters. The curve 820 generally consists of a series ofsmaller-scale peaks superimposed on a series of larger-scale peaks. Inthis example, the physiological phenomenon which results in thelarger-scale peaks has a greater effect on the measured phase of thetransmission coefficient and the effect occurs over a relatively longerperiod of time. In contrast, the physiological phenomenon which resultsin the smaller-scale peaks has a smaller effect on the measured phase ofthe transmission coefficient and the effect occurs over a relativelyshorter period of time.

The region 830 in the graph 810 includes three of the larger-scalepeaks. These peaks result from the respiration of the subject and theirfrequency is indicative of the respiration rate. Meanwhile, the region840 includes six of the smaller-scale peaks superimposed on a singlelarger-scale peak. These smaller-scale peaks are representative of theheart rate of the subject, which generally occurs on shorter time-scale,and causes smaller fluctuations in the phase of the transmissioncoefficient, than the respiration rate.

The graph 810 also includes a trend line 850. The trend of the curve 820is sensitive to the pulmonary artery pressure and/or the lung watercontent of the subject. As discussed further with respect to FIG. 9, thecurve 820 in FIG. 8 can be analyzed (e.g., by a digital signalprocessor) in order to determine the respiration rate, heart rate,stroke volume, cardiac output, and lung water content of the subject.The various peaks, trends, and other signal features can be isolatedfrom one another using known signal processing techniques. A processedsignal consisting predominantly of information from the smaller-scalepeaks in the region 840 can be referred to as a heart signal orwaveform; a processed signal consisting predominantly of informationfrom the larger-scale peaks in region 830 can be referred to as arespiration rate signal or waveform; a processed signal consistingpredominantly of trend information can be referred to as a lung watersignal or waveform; etc.

FIG. 9 illustrates how several physiological parameters can becalculated from a transmission coefficient signal (e.g., the phasecomponent of the signal), such as the one illustrated in FIG. 8. Theplot 910 is a magnified version of one cycle of the transmissioncoefficient signal. This can be extracted from the small signalvariation 840 in FIG. 8. The shaded portion of the graph corresponds tothe systolic phase (T_(s)), while the unshaded portion corresponds tothe diastolic phase (T_(d)). The graph shows both the systolic peak (SP)and the diastolic peak (DP). As illustrated in FIG. 9, the mean arterialpressure can be calculated from the diastolic peak and the systolicpeak. Alternatively, the mean arterial pressure is also related to thecardiac output (CO), the systemic vascular resistance (SVR), and thecentral venous pressure (CVP). The stroke volume (SV) can be calculatedfrom the length of the systolic phase and the diastolic phase. Thestroke volume also depends upon A_(s), which is the area under the curveduring the systolic phase. (If the parameter K in the equation forstroke volume is unknown, then stroke volume can instead be calculatedfrom cardiac output.) The cardiac output can be calculated from thestroke volume and the heart rate.

As discussed herein, one physiological characteristic which is ofclinical interest is lung water content. This information can be usedin, for example, the diagnosis and treatment of congestive heart failureor other medical conditions. Heart-related (cardiogenic) pulmonary edematypically occurs when the left ventricle of the heart is not able topump out blood at the same rate that it is received from the lungs. As aresult, pressure increases inside the left atrium and in the pulmonaryvasculature. This elevated pressure causes fluid to be pushed throughthe capillary walls into the air sacs of the lungs. Pulmonary edema, orexcess fluid in the lungs, can be a very serious medical condition.Thus, the ability to monitor lung water content can prove to be alife-saving technology. Signals such as the transmission coefficientsignals discussed herein can be used to monitor lung water content.Knowledge of lung water content is also important for patients withkidney disease and with Acute Respiratory Distress Syndrome (ARDS).Similar to the heart failure related medical complications, thesediseases are associated with accumulation of water in patients' lungsthat benefits from careful monitoring and management to prevent ahypotension condition, trauma, or even death.

FIG. 10 includes a pair of graphs which show the sensitivity of thephase of the transmission coefficient (lower graph 1010) when comparedto the pulmonary artery pressure (upper graph 1030) in a subject. (Theplot in FIG. 10 does not include the respiration and heart rate peaksshown in FIG. 8 because it has been processed to show changes in lungwater content vs. time (e.g., the trend line 850 in FIG. 8), not the rawtransmission coefficient signal vs. time.) The lower graph 1010 includesa curve 1020 which plots the phase of the transmission coefficientbetween two microwave sensors in the side-by-side configurationillustrated in FIG. 7 as a function of time. The upper graph 730includes a curve 1040 which plots the pulmonary artery pressure of thesubject as a function of time while fluid is infused into the subject.The arrows at the top of the graphs show when the infusion of fluidbegins, how much fluid is infused, and when the infusion ends. Asillustrated by the top graph 1030, the infusion of fluid into thesubject causes changes in the pulmonary artery pressure of the subject,resulting in changes in the phase of the microwave transmissioncoefficient (shown in the lower graph 1010).

Comparison of the lower graph 1010 to the upper graph 1030 reveals thatthe phase of the transmission coefficient is sensitive to changes inpulmonary artery pressure. Specifically, the phase of a sinusoidalsignal transmitted by one of the microwave sensors to the other throughthe thorax of the subject is retarded between 0-180°, depending on thepulmonary artery pressure. The phase of the transmission coefficientbecomes more negative when the pulmonary artery pressure increases. Inaddition, the slope of the phase graph goes toward zero when the slopeof the pulmonary artery pressure graph also goes toward zero (with thephase tending to bottom out where the pulmonary artery pressure peaks).Thus, there is a strong correlation and relationship (in this case, aninverse relationship, though that is not always the case, as discussedherein) between the phase of the transmission coefficient and thepulmonary artery pressure in this particular example. The sensitivity ofthe phase of the transmission coefficient to changes in pulmonary arterypressure is very good, as changes in the latter directly result inchanges to the former.

By measuring the phase of the transmission coefficient, it is thuspossible to detect changes in the pulmonary artery pressure, which isrelated to the lung water content. Since the transmission coefficientbetween two microwave sensors correlates relatively well (albeitinversely in the illustrated example) to changes in the pulmonaryarterial pressure and/or lung water content, the phase informationprovides the most sensitive indication to changes in lung water content,and hence the condition of the lung.

Although FIG. 10 illustrates a phase measurement for only a singlefrequency, in some embodiments, signals with multiple frequencycomponents can be transmitted and the phase of the transmissioncoefficient for each frequency component can be measured in order tomonitor pulmonary artery pressure and/or lung water content. For examplehigher frequencies may be used to emphasize surface and relativelyshallow sub-surface conditions, while lower frequencies will providedeeper penetration in the body and hence reflect and provide moreaccurate information about this region.

While changes in the phase of the transmission coefficient between twomicrowave sensors are correlated to changes in pulmonary artery pressureand/or lung water content, the manner in which the phase responds tochanges in pulmonary artery pressure and/or lung water content does notalways behave in the same way that is illustrated in FIG. 10. Forexample, in some instances, the phase of the transmission coefficientmay be directly correlated with pulmonary artery pressure, such that thephase advances in response to increases in pulmonary artery pressureand/or lung water content rather than retarding as in the illustratedexample. The precise nature of the change in the phase of thetransmission coefficient depends on a number of factors, including theplacement of the microwave sensors on the thorax of the subject.

However, the phase of the transmission coefficient is not the onlyinformation available from the measured microwave signal(s). Indeed, themagnitude(s) of one or more frequency components in the transmittedmicrowave signal can also be measured. As discussed further herein, themagnitude of a transmission coefficient can be used to indicate whethera change in the phase of the transmission coefficient is indicative ofimproving lung condition (e.g., decreased pulmonary artery pressureand/or lung water content) or worsening lung condition (e.g., increasedpulmonary artery pressure and/or lung water content).

As discussed with respect to FIGS. 8 and 9, the phase of thetransmission coefficient between two microwave sensors can be used tomeasure a number of other vital signs in addition to pulmonary arterypressure and/or lung water content. However, as is the case with respectto pulmonary artery pressure and/or lung water content, the placement ofthe microwave sensors can affect the overall accuracy and reliability ofthe measurements of such vital signs. The sensor placement locationwhich is best-suited to measure one vital sign may not be thebest-suited to measure another. For example, a pair of side-by-sidemicrowave sensors located with a clear “view” of the lung and minimalinterference from other organs (e.g., the heart) may be best-suited formeasuring lung water content. However, the same pair of sensors may notbe best-suited for measuring heart rate or respiration rate. In view ofthis variability based on microwave sensor placement on the thorax, itmay be advantageous for the monitoring system to include an array whichincludes additional microwave sensors placed at various locations on thethorax. By measuring the scattering parameters between each pair ofmicrowave sensors in the array, it may be possible to improve theaccuracy and reliability of various vital sign measurements. Forexample, different vital signs can be measured based on the scatteringparameters between different pairs of microwave sensors.

Furthermore, as discussed herein, the magnitude of a transmissioncoefficient can be used to indicate whether a change in phase isindicative of improving or worsening lung condition. In a system whichincludes an array with multiple pairs of microwave sensors, the phaseinformation can be obtained from the transmission coefficient between afirst pair of microwave sensors (e.g., a pair located proximate thelower portion of the lung where fluid is apt to pool), while themagnitude information can be obtained from the transmission coefficientbetween a second pair of microwave sensors (e.g., a pair located so asto have an even clearer “view” of the lung). It should be understood,however, that the magnitude information from the same microwave sensorpair can also be used in some embodiments to confirm whether themeasured phase information is indicative of improving or worsening lungcondition.

FIG. 11 illustrates an example of the placements of microwave sensors onthe thorax of a human for a monitoring system that includes an array ofmicrowave sensors. (The illustrated array of sensors can be used in thecalibration process described below.) Ten microwave sensors areillustrated and are numbered consecutively 1-10. Each microwave sensorhas a unique placement on the thorax. The placements of the tenmicrowave sensors are shown by anterior, posterior, left lateral, top,and 45° anterior-lateral views of the thorax. As illustrated, in someembodiments, a horizontal row of microwave sensors (1-8) can beprovided. Of these, three of the microwave sensors (1-3) are anteriorlylocated, three (4-6) are laterally located, and two (7-8) areposteriorly located. In addition to the horizontal row of microwavesensors, a sensor (9) is shown located nearer the lower extent of thelung and another sensor (10) is shown located nearer the heart. AlthoughFIG. 11 illustrates 10 microwave sensors, a greater or lesser number ofsensors can be used in different embodiments. Further, the specificplacements of the microwave sensors illustrated in FIG. 11 are examplesonly; different and/or additional placements can also be used dependingupon the application.

Of the placements illustrated in FIG. 11, microwave sensors 5-8 arethose which would generally be expected to have the most unobstructed“views” of the lung. They provide lateral and posterior “views” of thelung which are relatively unobstructed by other organs or tissues. Asdiscussed herein, in some embodiments, these sensors can advantageouslyprovide magnitude information which accurately indicates whethermeasured changes in phase information are indicative of improving orworsening lung condition.

FIG. 12 includes a graph 1200 of the magnitude (solid curve 1210) andphase (dotted curve 1220) of the transmission coefficient between thefifth and sixth microwave sensors illustrated in FIG. 11. These signalshave been processed to identify the trend line (e.g., similar to signal850 in FIG. 8). The graph 1200 shows the response of the magnitude andphase of the S(6,5) transmission coefficient (i.e., the output signalmeasured at sensor 6 when sensor 5 is excited with an input signal) tochanging fractional edema volume of a lung. As illustrated in FIG. 11,the fifth and sixth microwave sensors are adjacent sensors and arelaterally located on the thorax. As such, it is expected that thesesensors will have a relatively unobstructed “view” of the lung withoutsubstantial interference from other organs.

The graph 1200 shows that both the magnitude and phase of the S(6,5)transmission coefficient substantially monotonically decreased withincreasing fractional edema volume of the lung. The magnitude scale hasa range of 0.88 dB, while the phase scale has a range of 6.2°. Thus itmay be noted that the phase changes are larger in values (number ofdegrees) than the changes in the magnitude (in dB). This is oneindication that the phase is more sensitive to changes in lung water(while, as discussed further herein, the magnitude is more indicative ofwhether that change represents an increase or decrease in the amount oflung water).

FIG. 13 includes a graph 1300 of the magnitude (solid curve 1310) andphase (dotted curve 1320) of the transmission coefficient between thesixth and seventh microwave sensors illustrated in FIG. 11. The graph1300 shows the response of the magnitude and phase of the S(7,6)transmission coefficient (i.e., the output signal measured at sensor 7when sensor 6 is excited with an input signal) to changing fractionaledema volume of the lung. Once again, as illustrated in FIG. 11, thesixth and seventh microwave sensors are adjacent. The sixth sensor islocated laterally, while the seventh is located posteriorly. Again, itis expected that these sensors will have a relatively unobstructed“view” of the lung.

The graph 1300 is similar to the graph 1200 from FIG. 12 in that itshows that the magnitude of the transmission coefficient substantiallymonotonically decreased with increasing fractional edema volume of thelung. However, the graph 1300 is different from the graph 1200 in thatit shows that the phase of the transmission coefficient actuallyincreased with increasing fractional edema volume, rather thandecreasing as shown in FIG. 12. This illustrates the fact that the phaseresponse can vary depending on placement of the microwave sensors. Themagnitude scale in FIG. 13 has a range of 0.95 dB, while the phase scalehas a range of 3.2°.

FIG. 14 includes a graph 1400 of the magnitude (solid curve 1410) andphase (dotted curve 1420) of the transmission coefficient between theseventh and eighth microwave sensors illustrated in FIG. 11. The graph1400 shows the response of the magnitude and phase of the S(8,7)transmission coefficient (i.e., the output signal measured at sensor 8when sensor 7 is excited with an input signal) to changing fractionaledema volume of a lung. As illustrated in FIG. 11, the seventh andeighth microwave sensors are adjacent sensors and are posteriorlylocated on the thorax. Once again, it is expected that these sensorswill have a relatively unobstructed “view” of the lung.

The graph 1400 is similar to both FIGS. 12 and 13 in that it shows thatthe magnitude of the S(8,7) transmission coefficient substantiallymonotonically decreased with increasing fractional edema volume of thelung. Further, like FIG. 12, but unlike FIG. 13, the phase of the S(8,7)transmission coefficient substantially monotonically decreased withincreasing fractional edema volume. The magnitude scale in FIG. 14 has arange of 0.33 dB, while the phase scale has a range of 6.3°.

FIG. 15 includes a graph 1500 of the magnitude and phase of thetransmission coefficient between the sixth and seventh microwave sensorsillustrated in FIG. 11. These phase and magnitude changes are shown as afunction first of increasing edema (from 20% to 28%) and then decreasingedema (from 28% to 20%) in a lung. As in FIGS. 12-14, the magnitude ofthe transmission coefficient in FIG. 15 decreases as edema increases.FIG. 15 illustrates, however, that the magnitude of the transmissioncoefficient also increases as edema decreases.

FIGS. 12-14 show results from the same increase in lung water content,but the measured phase (while indicating in every case that changes inlung water were occurring) showed changes in two different directions.FIGS. 12-14 show that the phases of transmission coefficients S(6,5) andS(8,7) both had a negative slope as lung water content increased.However, the phase of transmission coefficient S(7,6) increased withincreasing lung water content. Notwithstanding the different behaviorsof the phases in these figures, the commonality between all threefigures is that the slopes of the magnitudes of the transmissioncoefficients S(6,5), S(7,6), and S(8,7) all decreased with increasinglung water content. This is likely due to the fact that increased lungwater content causes more attenuation in the microwave signals,resulting in a decrease in the measured magnitudes of the transmittedmicrowave signals. Conversely, decreased lung water content would causeless attenuation in the microwave signals, resulting in a relativeincrease in the measured magnitudes of the transmitted microwavesignals. Although this relationship between magnitude and lung watercontent may not necessarily be as well-defined for microwave sensorswithout a clear “view” of the lung due to electromagnetic scattering andinterference effects from other organs and tissues, it does appear tohold true at least for sensors located in the clear viewing section forthe lung. Thus, in some embodiments, the clear viewing of a section ofthe lung is important because of the correlation of the magnitudeinformation from those sensors with changes in the amount of fluidaccumulation in the lung. On the other hand, microwave sensors locatedin other positions may be better suited for providing information aboutother vital signs.

As discussed herein, in some embodiments, phase information—rather thanmagnitude information—from the microwave sensors can be most sensitivelycorrelated with changes in lung water content and/or related metrics.However, as just discussed with respect to FIGS. 12-14, the phaseinformation may be ambiguous in that, in some situations, neitherpositive nor negative changes in phase may be reliably indicative ofimproving or worsening lung condition. This can be so because phase is arelative parameter (i.e., an advance or delay with respect to areference phase). Therefore, the phase may change in the positive ornegative direction with a change in lung water content depending uponthe reference phase. The reference phase, however, may depend on thesize of the patient, sensor location, and even the sizes and locationsof organs within the patient's body, resulting in possible ambiguity inthe meaning of the phase measurements. The possible ambiguity of thephase information is not problematic when other independent informationis available to help determine the condition of the lung. However, thepossible ambiguity of the phase information can potentially beproblematic in cases of stand-alone microwave monitoring, where noadditional information is provided from a catheter or other comparativeinstrument.

However, since the magnitudes of transmission coefficients betweenmicrowave sensors located in the clear viewing section for the lungreliably decrease with increased lung water content, and converselyincrease with decreased lung water content, such magnitude informationcan be used in conjunction with phase information to both sensitivelydetect changes in lung water content and determine whether those changesindicate improving or worsening lung condition. As a solution to thepotential problem of phase information ambiguity, magnitude informationcan be used to clarify whether a change in lung water content indicatedby a phase change is indicative of increasing or decreasing lung watercontent (or a related parameter).

In some embodiments, one or more microwave signals are transmitted intothe thorax of a patient using one or more microwave sensors, asdiscussed herein. This can include, for example, a microwave signaltransmitted through the thorax between side-by-side microwave sensors.The raw signal can then be pre-processed, as described herein, to obtaininformation indicative of lung water content (e.g., trend line data canbe obtained from the raw signal). The phase information can then beanalyzed to determine whether the lung water content (or a relatedparameter) has changed. For example, a digital signal processor cananalyze the slope of the phase information of the lung water signal overtime to determine whether the phase is increasing or decreasing. Asdiscussed herein, such fluctuations may reliably be correlated withchanges in lung water content. Meanwhile, the magnitude of one or moremicrowave signals can be analyzed (e.g., by a digital signal processor)to determine whether a change indicated by the phase information isindicative that lung water content (or a related parameter) isincreasing or decreasing.

For example, the slope of the magnitude information of the lung watersignal over time can be analyzed to determine whether the magnitudeinformation is increasing or decreasing. If the magnitude information isdecreasing over time (i.e., greater attenuation of the microwavesignal), then the digital signal processor may determine that the changein phase information is indicative of increased lung water content andworsening lung condition. Alternatively, if the magnitude information isincreasing over time (i.e., less attenuation of the microwave signal),then the digital signal processor may determine that the change in phaseinformation is indicative of decreased lung water content and improvinglung condition. The digital signal processor can then provide anappropriate output signal to a display, a light, a speaker, etc. toindicate that the lung water content (or a related parameter) isimproving or worsening.

In some cases, the magnitude information may be obtained from microwavesensors in the clear viewing section for the lung (e.g., the sensors maybe laterally or posteriorly located with respect to the lung). Themagnitude information may be obtained from the same pair of microwavesensors used to provide the phase information. Alternatively, themagnitude information may be obtained from a different pair of sensors.In addition, the phase and magnitude information may be obtained andanalyzed at a single frequency (e.g., 915 MHz or 2.4 GHz) or at multiplefrequencies. The measured frequency or frequencies can be the same ordifferent for the phase and magnitude information, respectively.

In some embodiments, specific microwave sensors can be selected a priorifor making the vital sign measurements discussed herein. The same ordifferent sensors can be used for different vital sign measurements, orfor different aspects of a single vital sign measurement (e.g., forproviding the phase and magnitude information in a lung watermeasurement). However, in other embodiments, specific microwave sensorsare not selected a priori. Instead, an automated calibration method canbe performed in order to select which microwave sensors are used toperform a given vital sign measurement. This can be advantageous in someembodiments due to, for example, variations in sensor placement and/orpatient size. In some embodiments, the automated calibration method caninclude performing a scan of the microwave scattering parameters for thearray of microwave sensors.

FIG. 16 is a chart of the magnitude and phase of the complete set ofscattering parameters for a monitoring system which includes an array ofmicrowave sensors. FIG. 16 illustrates the magnitude and phase valuesfor the transmission coefficients between each pair of microwave sensorsat one moment in time. It also illustrates the magnitude and phasevalues for the reflection coefficients of each individual microwavesensor at one moment in time. Although the chart in FIG. 15 includesmeasurements for all of the transmission and reflection coefficients forthe array of microwave sensors, in some embodiments only thetransmission coefficients for adjacent side-by-side pairs of microwavesensors are obtained.

The information shown in FIG. 16, or a subset thereof, can be obtainedfor a single frequency or for multiple different frequencies. Inaddition, it can be obtained at a single instant in time or at multipleinstants over the course of a period of time to obtain a collection ofscattering parameter signals. Once all or a portion of the scatteringparameter information has been obtained, it can be analyzed (e.g., by adigital signal processor) to select which microwave sensor data will beused to perform a given vital sign measurement.

In some embodiments, microwave sensor data can be selected for use in aparticular vital sign measurement based on how closely a parametercalculated from the data set in question correlates with a known ormeasured physiological characteristic at an initial time or on acontinuing basis. For example, the signal from the pair of microwavesensors which yields a mean arterial blood pressure (MAP) measurement(e.g., calculated as discussed with respect to FIG. 9) which mostclosely correlates with an initial or continued reference MAPmeasurement can be selected. In some cases, the reference MAPmeasurement can be obtained from another instrument, such as a catheterinserted into the patient's body. Correlation to mean arterial bloodpressure is just one example of a physiological criterion which can beused to guide the selection of sensor data for calculating a given vitalsign. Other physiological criteria can also be used.

As just mentioned, microwave sensor data can be selected for use in aparticular vital sign measurement based on the data's correlation to ameasurement of a physiological characteristic, such as mean arterialpressure, from an external device. However, in some embodiments,microwave sensor data can also be selected based on its correlation tothe data obtained from other pairs of sensors in the microwave array.For example, mean arterial pressure can be determined based on datacollected from one pair of microwave sensors in the array. As discussedherein (e.g., with respect to FIG. 9), mean arterial pressure can beobtained from a measured heart waveform. In some embodiments, themeasured heart waveform may be obtained from the microwave sensor pairlocated nearest the heart.

Once the heart waveform has been obtained, the mean arterial pressurecan be calculated and designated as a standard to be compared with datafrom other microwave sensors in the array. For example, as discussedherein, data from sensors located with a “view” of the lung can be usedto determine whether lung water content is changing and whether thecondition of the lung is improving or worsening. If more than one pairof sensors has a “view” of the lung, in some embodiments, the data fromeach such pair of sensors can be correlated with the designated standardmean arterial pressure measurement (whether determined from an externalinstrument or from the microwave system itself). This can be done, forexample, by determining one or more additional mean arterial pressurevalues from the waveforms obtained from the sensors with a “view” of thelung. These arterial pressure values can be compared with the designatedstandard arterial pressure value. The data from the pair of sensorswhich is designated as correlating best with the standard mean arterialpressure value (e.g., as determined using known statistical and signalprocessing techniques) can be selected by the processor as the data mostindicative of the condition of the lung because lung water content iscorrelated with arterial pressure. The processor can analyze theselected data to monitor lung water content in the patient.

FIG. 17 includes a graph of a transmission coefficient signal (e.g., thephase component of the signal) corresponding to a heart waveform for adialysis patient. The graph includes a first curve 1710 which wasmeasured at the start of the dialysis process, a second curve 1720measured in the middle of dialysis, and a third curve 1730 measured atthe end of dialysis. These curves show that the magnitude and shape ofthe heart waveform changes with changing blood pressure during thedialysis process. This data provides further evidence that a heartwaveform obtained using the microwave system described herein can beused to determine a measure of arterial pressure. Thus, in someembodiments, a processor analyzes the heart waveform (including itsmagnitude, shape, and other characteristics) to determine the bloodpressure of the patient. This can be done using, for example, thetechnique described and shown with respect to FIG. 9. As just discussed,this measurement can be used in a calibration process to select datafrom other sensors in the array from which to monitor edema of thelungs.

FIGS. 18A and 18B also show clinical data collected from a dialysispatient using the microwave system described herein. FIG. 18A includes agraph 1810 of the phase of a raw transmission coefficient signalcollected using the microwave system. A similar raw phase signal isshown in graph 1810 of FIG. 18B. The raw transmission coefficient signalin graph 1810 was processed, using the techniques disclosed herein, toobtain the heart waveform shown in graph 1820. A similar heart waveformis shown in graph 1820 in FIG. 18B. (FIG. 18B also shows a possibleintermediate step of calculating a signal shown in graph 1815, whichincludes a heart waveform superimposed on a breathing waveform.) Afterthe heart waveform in graph 1820 was obtained, it was processed, usingthe techniques disclosed herein, to obtain a mean arterial pressurewaveform which is shown in graph 1830. The mean arterial pressurewaveform in graph 1830 shows that the dialysis patient's blood pressuredecreased from time A to time B to time C as the volume of the patient'sblood was reduced due to the dialysis process.

FIG. 18A also shows magnified views of the heart (cardiac) waveform attime A (shown in graph 1822), time B (shown in graph 1824), and time C(shown in graph 1826). These magnified views of the heart waveform showthat its peak-to-trough amplitude was greatest at time A when thepatient's mean arterial pressure was the highest, that thepeak-to-trough amplitude was smaller at time B when the patient's meanarterial pressure had been reduced due to decreased blood volume, andthat the peak-to-trough amplitude was smallest at time C when thepatient's mean arterial pressure was likewise the smallest. These heart(cardiac) waveforms are representative of Starling's Law, whichgenerally provides that the stroke volume of the heart increases withincreasing blood volume and decreases with decreasing blood volume. Inother words, the strength with which the left ventricle contractsincreases with increasing end atrial diastolic volume and decreases withdecreasing end atrial diastolic volume. This clinical data providesfurther confirmation that the heart (cardiac) waveforms measured by themicrowave system described herein can provide extremely valuableclinical data.

FIG. 19 shows a graphical representation of Starling's Law andillustrates how the microwave system described herein can be used toassist in treatment of patients with congestive heart failure orpatients undergoing dialysis. The graph 1900 in FIG. 19 plots strokevolume as a function of left ventricular end diastolic pressure. Asshown by curves 1910, 1920, in 1930, stroke volume increases withincreasing end diastolic pressure in accordance with Starling's Law.When diastolic pressure is too low, the patient is exhibitinghypotension, as shown by the shaded region 1940. When diastolic pressureincreases beyond the limits of the heart's ability to further increasestroke volume, the curves 1910, 1920, and 1930 begin to level off. Whenthis occurs, pressure increases in the pulmonary vasculature, whichcauses fluid to pass through the capillary walls into the lungsresulting in pulmonary congestion. This is shown by the shaded region1950.

Point a on the middle curve 1920 is representative of the normaloperating condition of the heart in a normal patient. The top curve 1910is that of a patient whose heart is exhibiting higher-than-normalcontractility. Meanwhile, point c on the bottom curve 1930 isrepresentative of the operating condition of a patient who isexperiencing heart failure and associated pulmonary congestion. Thiscondition represents a medical emergency which can be relieved byreducing end diastolic pressure, such as for example by reducing thepatient's blood volume using diuretics or other techniques. The goal ofsuch treatment is to cause the patient's heart to transition towardpoint b on the lower curve 1930, as illustrated by the arrow. However,as is evident from the graph, if the treatment is taken too far thepatient will experience hypotension. It would therefore be advantageousto use the signals provided by the microwave system described herein toprovide real-time monitoring and feedback regarding the efficacy of thetreatment for congestive heart failure. This can be done by, forexample, monitoring the peak-to-trough amplitude of the heart signalsshown in FIG. 18A. Similarly, this technique can be used to preventhypotension in dialysis patients. The microwave system described hereinis particularly advantageous for these and other applications because itis capable of providing real-time, non-invasive, accurate data regardingthe physiological condition of the heart, lungs, and vasculature.

In some embodiments, isolated lung experiments can be performed in orderto understand, quantify, and/or calibrate the impact of various diseaseson lung water content, the distribution of water in the lung, and theeffect of such processes on the signals measured by the microwave systemdescribed herein. In such embodiments, a lung can be removed andisolated from a subject. Blood or other fluid can be infused directlyinto the isolated lung using a pump. The pump can also pump fluid out ofthe isolated lung as desired. The isolated lung can be positioned on ascale and the weight of the lung can be used as a control measurement ofthe lung water content at any point during the experiment. The isolatedlung can also be connected to a mechanical respirator which pumps airinto the isolated lung in order to simulate respiration during theexperiment. Microwave sensors can be placed directly on the isolatedlung to collect data, as described herein, throughout the experiment.This type of isolated lung experiment can be a valuable tool fordeveloping an understanding of the effect of lung water contentclinically and physiologically.

In some embodiments, when an array of microwave sensors is used in themicrowave instrument disclosed herein, the array of received signals maybe combined using a reconstruction algorithm to provide an image of thewater distribution in the lung. Different sensors in the array can beexcited at different frequencies to allow, for example, targetedmeasurement of specific vital signs. For example, an anterior sensor inthe array can be excited at 2.4 GHz to measure heart rate. The same or adifferent anterior sensor can be excited at 915 MHz to measure breathingrate. A lateral or posterior sensor in the array can be excited at 915MHz to perform a lung water measurement, etc. It should be understood,however, that these are only examples; different frequencies besides theones mentioned can be used. Further, microwave sensors located indifferent positions than the ones just mentioned can be used to performvarious vital sign measurements.

The embodiments described throughout the attached specification,drawings, and claims have been described at a level of detail to allowone of ordinary skill in the art to make and use the devices, systems,methods, etc. described herein. A wide variety of variation is possible.Components, elements, and/or steps may be altered, added, removed, orrearranged. For example, method steps can be practiced all together orin any sub-combination. Similarly, claim limitations can be separatedand/or combined and included in any combination or sub-combination.

The devices, systems, and methods described herein can advantageously beimplemented using, for example, computer software, hardware, firmware,or any combination of software, hardware, and firmware. Software modulescan comprise computer executable code for performing the functionsdescribed herein. In some embodiments, computer-executable code isexecuted by one or more general purpose computers (including desktopcomputers, notebook computers, tablet computers, smart phones, etc).However, a skilled artisan will appreciate, in light of this disclosure,that any module that can be implemented using software to be executed ona general purpose computer can also be implemented using a differentcombination of hardware, software, or firmware. For example, such amodule can be implemented completely in hardware using a combination ofintegrated circuits. Alternatively or additionally, such a module can beimplemented completely or partially using specialized computers designedto perform the particular functions described herein rather than bygeneral purpose computers. In addition, where methods are described thatare, or could be, at least in part carried out by computer software, itshould be understood that such methods can be provided on non-transitorycomputer-readable media (e.g., optical disks such as CDs or DVDs, harddisk drives, flash memories, diskettes, or the like) that, when read bya computer or other processing device, cause it to carry out the method.

A skilled artisan will also appreciate, in light of this disclosure,that multiple distributed computing devices can be substituted for anyone computing device illustrated herein. In such distributedembodiments, the functions of the one computing device are distributedsuch that some functions are performed on each of the distributedcomputing devices.

The devices described herein can exchange information with each other,or with other devices, via one or more communication channels. Suchcommunication channels can be wired or wireless, and can includenetworks, such as a Local Area Network, a Wide Area Network, theInternet, etc.

While certain embodiments have been explicitly described, otherembodiments will become apparent to those of ordinary skill in the artbased on this disclosure. Therefore, the scope of the invention isintended to be defined by reference to the claims and not simply withregard to the explicitly described embodiments.

What is claimed is:
 1. A method of monitoring lung water content of apatient using a plurality of microwave sensors, the method comprising:transmitting a plurality of microwave signals into the thorax of apatient using the microwave sensors; receiving a plurality of themicrowave signals using the microwave sensors, the plurality of receivedmicrowave signals each comprising at least one frequency componenthaving a magnitude and a phase; analyzing the phase of the receivedmicrowave signal corresponding to a first pair of the microwave sensorsto monitor changes in the lung water content; and analyzing themagnitude of the received microwave signal corresponding to a second,different pair of the microwave sensors to determine whether the changein lung water content indicated by the received microwave signalcorresponding to the first pair of microwave sensors is increasing ordecreasing.
 2. The method of claim 1, further comprising: determiningthat the lung water content is increasing if the magnitude isdecreasing; and determining that the lung water content is decreasing ifthe magnitude is increasing.
 3. The method of claim 1, wherein thesecond pair of microwave sensors is located laterally or posteriorly onthe patient's thorax in a viewing area for the lung that is unobstructedby another internal organ.
 4. The method of claim 1, further comprising:analyzing the received microwave signal corresponding to a pair of themicrowave sensors located adjacent to the heart of the patient todetermine a blood pressure indicator.
 5. The method of claim 4, furthercomprising selecting the received microwave signal corresponding to thesecond pair of microwave sensors based on correlation with the bloodpressure indicator.
 6. The method of claim 1, wherein the transmittedmicrowave signals comprise different frequencies.
 7. The method of claim1, wherein the received microwave signals each correspond to adjacentpairs of microwave sensors.
 8. The method of claim 1, whereintransmitting the microwave signals into the thorax of the patient usingthe microwave sensors comprises locally coupling the microwave signalsinto the body without leakage into an adjacent microwave sensor.
 9. Themethod of claim 1, further comprising determining the lung water contentusing one or more of the received microwave signals.
 10. A system formonitoring lung water content of a patient, the system comprising: aplurality of microwave sensors; and a processor configured to cause oneor more of the microwave sensors to transmit a plurality of microwavesignals into the thorax of a patient; receive a plurality of of themicrowave signals from one or more of the microwave sensors, theplurality of received microwave signals each comprising at least onefrequency component having a magnitude and a phase; analyze the phase ofthe received microwave signal corresponding to a first pair of themicrowave sensors to monitor changes in the lung water content; andanalyze the magnitude of the received microwave signal corresponding toa second, different pair of the microwave sensors to determine whetherthe change in lung water content indicated by the received microwavesignal corresponding to the first pair of microwave sensors isincreasing or decreasing.
 11. The system of claim 10, wherein theprocessor is further configured to: determine that the lung watercontent is increasing if the magnitude is decreasing; and determine thatthe lung water content is decreasing if the magnitude is increasing. 12.The system of claim 10, wherein the second pair of microwave sensors islocated laterally or posteriorly on the patient's thorax in a viewingarea for the lung that is unobstructed by another internal organ. 13.The system of claim 10, wherein the processor is further configured to:analyze the received microwave signal corresponding to a pair of themicrowave sensors located adjacent to the heart of the patient todetermine a blood pressure indicator.
 14. The system of claim 13,wherein the processor is further configured to select the receivedmicrowave signal corresponding to the second pair of microwave sensorsbased on correlation with the blood pressure indicator.
 15. The systemof claim 10, wherein the transmitted microwave signals comprisedifferent frequencies.
 16. The system of claim 10, wherein the receivedmicrowave signals each correspond to adjacent pairs of microwavesensors.
 17. The system of claim 10, wherein the microwave sensors aretransmission line-based.
 18. The system of claim 10, wherein theprocessor is further configured to determine the lung water contentusing one or more of the received microwave signals.
 19. The system ofclaim 10, wherein the microwave sensors in each pair are providedadjacent to one another on a patch.